concurrency control - stanford university · concurrency control + recovery beyond serializability...

Concurrency Control

Instructor: Matei Zahariacs245.stanford.edu

https://cs245.stanford.edu/

OutlineWhat makes a schedule serializable?Conflict serializability

Precedence graphsEnforcing serializability via 2-phase locking» Shared and exclusive locks» Lock tables and multi-level locking

Optimistic concurrency with validation

Concurrency control + recoveryBeyond serializabilityCS 245 2

Which Objects Do We Lock?

?

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Table A

Table B

...

Tuple ATuple BTuple C

...

Disk block

A

Disk block

B

...

DB DB DB

Idea: Multi-level locking

Example

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R1

t1t2 t3 t4

Example

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R1

t1t2 t3 t4

T1(IS)

T1(S)

Example

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R1

t1t2 t3 t4

T1(IS)

T1(S)

, T2(S)

Example 2

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R1

t1t2 t3 t4

T1(IS)

T1(S)

Example 2

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R1

t1t2 t3 t4

T1(IS)

T1(S)

, T2(IX)

T2(X)

Example 3

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R1

t1t2 t3 t4

T1(IS)

T1(S)

, T2(S), T3(IX)?

compat RequestorIS IX S SIX X

ISHolder IX

SSIX

X

T T T T FFFFFFFFF

FFFTFTFTFFTT

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Multiple Granularity Locks

Parent Child can be lockedlocked in by same transaction in

ISIXSSIXX

P

C

IS, SIS, S, IX, X, SIXnoneX, IX, SIXnone

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Rules Within A Transaction

Multi-Granularity 2PL Rules1. Follow multi-granularity compat function2. Lock root of tree first, any mode3. Node Q can be locked by Ti in S or IS only if

parent(Q) locked by Ti in IX or IS4. Node Q can be locked by Ti in X, SIX, IX only if

parent(Q) locked by Ti in IX, SIX5. Ti is two-phase6. Ti can unlock node Q only if none of Q’s

children are locked by Ti

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Exercise:Can T2 access object f2.2 in X mode? What locks will T2 get?

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R1

t1t2 t3 t4T1(IX)

f2.1 f2.2 f3.1 f3.2

T1(IX)

T1(X)


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R1

t1t2 t3 t4T1(X)

f2.1 f2.2 f3.1 f3.2

T1(IX)


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R1

t1t2 t3 t4T1(S)

f2.1 f2.2 f3.1 f3.2

T1(IS)

Exercise:Can T2 access object f2.2 in S mode? What locks will T2 get?

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R1

t1t2 t3 t4T1(IX)

f2.1 f2.2 f3.1 f3.2

T1(SIX)

T1(X)


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R1

t1t2 t3 t4T1(IX)

f2.1 f2.2 f3.1 f3.2

T1(SIX)

T1(X)

Insert + Delete Operations

Insert

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A

Za

...

Changes to Locking Rules:

1. Get exclusive lock on A before deleting A

2. When Ti inserts an object A, Ti receives an exclusive lock on A

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Still Have Problem: Phantoms

Example: relation R (id, name,…)constraint: id is unique keyuse tuple locking

R id name ….o1 55 Smitho2 75 Jones

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T1: Insert <12,Mary,…> into RT2: Insert <12,Sam,…> into R

T1 T2l-S1(o1) l-S2(o1)l-S1(o2) l-S2(o2)Check Constraint Check Constraint

Insert o3[12,Mary,..]Insert o4[12,Sam,..]

... ...

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Solution

Use multiple granularity tree

Before insert of node N,lock parent(N) in X mode

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R1

t1 t2 t3

Back to ExampleT1: Insert<12,Mary> T2: Insert<12,Sam>

T1 T2l-X1(R)

Check constraintInsert<12,Mary>U1(R)

l-X2(R)Check constraintOops! id=12 already in R!

l-X2(R) delayed

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Instead of Locking R, Can Use Index Nodes for Ranges

Example:

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...

...

...

R

Index100<id≤200

Index0<id≤100

id=2 id=5 id=107 id=109

How Is Locking Implemented In Practice?Every system is different (e.g., may not even provide conflict serializable schedules)

But here is one (simplified) way ...

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Sample Locking System

1. Don’t ask transactions to request/release locks: just get the weakest lock for each action they perform

2. Hold all locks until the transaction commits

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#locks

time

Sample Locking System

Under the hood: lock manager that keeps track of which objects are locked» E.g. hash table

Also need good ways to block transactions until locks are available, and to find deadlocks

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Validation ApproachTransactions have 3 phases:

1. Read» Read all DB values needed» Write to temporary storage» No locking

2. Validate» Check whether schedule so far is serializable

3. Write» If validate OK, write to DB

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Key Idea

Make validation atomic

If the validation order is T1, T2, T3, …, then resulting schedule will be conflict equivalent to Ss = T1, T2, T3, …

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Implementing Validation

System keeps track of two sets:

FIN = transactions that have finished phase 3(write phase) and are all done

VAL = transactions that have successfullyfinished phase 2 (validation)

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Example That Validation Must Prevent:

RS(T2)={B} RS(T3)={A,B}

WS(T2)={B,D} WS(T3)={C}

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time

T2start

T2validated

T3validated

T3start

Ç≠ ∅

T2finish

phase 3

Example That Validation Must Allow:

RS(T2)={B} RS(T3)={A,B}

WS(T2)={B,D} WS(T3)={C}

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time

T2start

T2validated

T3validated

T3start

Ç≠ ∅

Another Thing Validation Must Prevent:

RS(T2)={A} RS(T3)={A,B}

WS(T2)={D,E} WS(T3)={C,D}

time

T2validated

T3validated

finishT2

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RS(T2)={A} RS(T3)={A,B}


time

T2validated

T3validated

finishT2

BAD: w3(D) w2(D)

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Another Thing Validation Must Prevent:

RS(T2)={A} RS(T3)={A,B}


time

T2validated

T3validated

finishT2

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Another Thing Validation Must Allow:

Validation Rules for Tj:

when Tj starts phase 1: ignore(Tj) ¬ FIN

at Tj Validation:if Check(Tj) then

VAL ¬ VAL ∪ {Tj}do write phaseFIN ¬ FIN ∪ {Tj}

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Check(Tj)

for Ti Î VAL – ignore(Tj) doif (WS(Ti) ∩ RS(Tj) ≠ ∅ or

(Ti Ï FIN and WS(Ti) ∩ WS(Tj) ≠ ∅))then return false

return true

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Exercise

T: RS(T)={A,B}WS(T)={A,C}

V: RS(V)={B}WS(V)={D,E}

U: RS(U)={B}WS(U)={D}

W: RS(W)={A,D}WS(W)={A,C}

startvalidatefinish

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Is Validation = 2PL?

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2PLVal

2PLVal

2PLVal

Val2PL

S: w2(y) w1(x) w2(x)

Achievable with 2PL?

Achievable with validation?

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S: w2(y) w1(x) w2(x)

S can be achieved with 2PL:l2(y) w2 (y) l1(x) w1(x) u1(x) l2(x) w2(x) u2(x) u2(y)

S cannot be achieved by validation:The validation point of T2, val2, must occur before w2(y) since transactions do not write to the database until after validation. Because of the conflict on x, val1 < val2, so we must have something like:

S: val1 val2 w2(y) w1(x) w2(x)

With the validation protocol, the writes of T2 should not start until T1 is all done with writes, which is not the case.

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Validation Subset of 2PL?Possible proof (Check!):» Let S be validation schedule» For each T in S insert lock/unlocks, get S’:

• At T start: request read locks for all of RS(T)• At T validation: request write locks for WS(T);

release read locks for read-only objects• At T end: release all write locks

» Clearly transactions well-formed and 2PL» Must show S’ is legal (next slide)

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Say S’ not legal (due to w-r conflict):S’: ... l1(x) w2(x) r1(x) val1 u1(x) ...» At val1: T2 not in Ignore(T1); T2 in VAL» T1 does not validate: WS(T2) Ç RS(T1) ¹ Æ» contradiction!

Say S’ not legal (due to w-w conflict):S’: ... val1 l1(x) w2(x) w1(x) u1(x) ...» Say T2 validates first (proof similar if T1 validates first)» At val1: T2 not in Ignore(T1); T2 in VAL» T1 does not validate:

T2 Ï FIN AND WS(T1) Ç WS(T2) ¹ Æ)» contradiction!

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Validation Subset of 2PL?

Is Validation = 2PL?

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2PLVal

2PLVal

2PLVal

Val2PL

When to Use Validation?

Validation performs better than locking when:» Conflicts are rare» System resources are plentiful» Have tight latency constraints

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Example: Tj Ti

wj(A)ri(A)

Commit Ti

Abort Tj

Concurrency Control & Recovery

……

… ……

…

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Non-persistent commit (bad!)avoided byrecoverableschedules

Example: Tj Ti

wj(A)ri(A)wi(B)

Abort Tj[Commit Ti]

……

…

……

…

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Concurrency Control & Recovery

Cascading rollback (bad!)avoided byavoids-cascading-rollback (ACR)schedules

Core Problem

Schedule is conflict serializable

Tj Ti

But not recoverable

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To Resolve This

Need to mark the “final” decision for each transaction in our schedules:» Commit decision: system guarantees

transaction will or has completed» Abort decision: system guarantees

transaction will or has been rolled back

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Model This as 2 New Actions:

ci = transaction Ti commits

ai = transaction Ti aborts

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......

......

Tj Ti

wj(A)ri(A)

ci ¬ can we commit here?

Back to Example

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DefinitionTi reads from Tj in S (Tj ÞS Ti) if:

1. wj(A) <S ri(A)

2. aj <S r(A) (<S: does not precede)

3. If wj(A) <S wk(A) <S ri(A) then ak <S ri(A)

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Definition

Schedule S is recoverable if

whenever Tj ÞS Ti and j ¹ i and ci Î S

then cj <S ci

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Notes

In all transactions, reads and writes must precede commits or abortsó If ci Î Ti, then ri(A) < ai, wi(A) < ai

ó If ai Î Ti, then ri(A) < ai, wi(A) < ai

Also, just one of ci, ai per transaction

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How to Achieve Recoverable Schedules?

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With 2PL, Hold Write Locks Until Commit (“Strict 2PL”)

Tj Ti

Wj(A)

Cj

uj(A)ri(A)

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......

......

......

With Validation, No Change!

Each transaction’s validation point is its commit point, and only write after

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DefinitionsS is recoverable if each transaction commits only after all transactions from which it read have committed

S avoids cascading rollback if each transaction may read only those values written by committed transactions

S is strict if each transaction may read and write only items previously written by committed transactions (≡ strict 2PL)CS 245 61

Relationship of Recoverable, ACR & Strict Schedules

Avoids cascading rollback

Recoverable

ACR

Strict

Serial

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ExamplesRecoverable:

w1(A) w1(B) w2(A) r2(B) c1 c2

Avoids Cascading Rollback:w1(A) w1(B) w2(A) c1 r2(B) c2

Strict:w1(A) w1(B) c1 w2(A) r2(B) c2

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Recoverability & Serializability

Every strict schedule is serializable

Proof: equivalent to serial schedule based on the order of commit points» Only read/write from previously committed

transactions

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Recoverability & Serializability

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Concurrency control + recoveryBeyond serializability

66

Weaker Isolation Levels

Dirty reads: Let transactions read values written by other uncommitted transactions» Equivalent to having long-duration write locks,

but no read locks

Read committed: Can only read values from committed transactions, but they may change» Equivalent to having long-duration write locks

(X) and short-duration read locks (S)

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Repeatable reads: Can only read values from committed transactions, and each value will be the same if read again» Equivalent to having long-duration read &

write locks (X/S) but not table locks for insert

Remaining problem: phantoms!

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Snapshot isolation: Each transaction sees a consistent snapshot of the whole DB (as if we saved all committed values when it began)» Often implemented with multi-version

concurrency control (MVCC)

Still has some anomalies! Example?

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Snapshot isolation: Each transaction sees a consistent snapshot of the whole DB (as if we saved all committed values when it began)» Often implemented with multi-version

concurrency control (MVCC)

Write skew anomaly: txns write different values» Constraint: A+B ≥ 0» T1: read A, B; if A+B ≥ 1, subtract 1 from A» T2: read A, B; if A+B ≥ 1, subtract 1 from B» Problem: what if we started with A=1, B=0?

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Interesting Fact

Oracle calls their snapshot isolation level “serializable”, and doesn’t provide serializable

Many other systems provide snapshot isolation as an option» MySQL, PostgreSQL, MongoDB, SQL Server

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